Preservation of dependence concepts under bivariate weighted distributions

2015 ◽  
Vol 45 (15) ◽  
pp. 4589-4599 ◽  
Author(s):  
S. Izadkhah ◽  
M. Amini ◽  
G. R. Mohtashami Borzadaran
Keyword(s):  
Weighted Distributions ◽  
Dependence Concepts

scholarly journals Semiparametric estimation for count data through weighted distributions

2009 ◽  
Vol 139 (10) ◽  
pp. 3625-3638 ◽  
Author(s):  
C.C. Kokonendji ◽  
T. Senga Kiessé ◽  
N. Balakrishnan
Keyword(s):  
Count Data ◽  
Semiparametric Estimation ◽  
Weighted Distributions

scholarly journals On the distance between convex-ordered random variables, with applications

2002 ◽  
Vol 34 (2) ◽  
pp. 349-374 ◽  
Author(s):  
Michael V. Boutsikas ◽  
Eutichia Vaggelatou
Keyword(s):  
Random Variables ◽  
Simple Approximation ◽  
Negative Dependence ◽  
Exponential Approximation ◽  
Probability Metrics ◽  
Convex Ordering ◽  
Compound Poisson ◽  
Approximation Techniques ◽  
Negatively Dependent Random Variables ◽  
Dependence Concepts

Simple approximation techniques are developed exploiting relationships between generalized convex orders and appropriate probability metrics. In particular, the distance between s-convex ordered random variables is investigated. Results connecting positive or negative dependence concepts and convex ordering are also presented. These results lead to approximations and bounds for the distributions of sums of positively or negatively dependent random variables. Applications and extensions of the main results pertaining to compound Poisson, normal and exponential approximation are provided as well.

scholarly journals Form-Invariance of the Non-Regular Exponential Family of Distributions

2018 ◽  
Vol 41 (2) ◽  
pp. 157-172
Author(s):  
Samereh Ghorbanpour ◽  
Rahim Chinipardaz ◽  
Seyed Mohammad Reza Alavi
Keyword(s):  
Exponential Family ◽  
Information Matrix ◽  
Likelihood Estimation ◽  
Weight Functions ◽  
Weighted Distribution ◽  
Weighted Distributions ◽  
Original Distribution ◽  
Special Cases ◽  
Exponential Family Of Distributions ◽  
Regular Family

The weighted distributions are used when the sampling mechanism records observations according to a nonnegative weight function. Sometimes the form of the weighted distribution is the same as the original distribution except possibly for a change in the parameters that is called the form-invariant weighted distribution. In this paper, by identifying a general class of weight functions, we introduce an extended class of form-invariant weighted distributions belonging to the non-regular exponential family which included two common families of distribution: exponential family and non-regular family as special cases. Some properties of this class of distributions such as the sufficient and minimal sufficient statistics, maximum likelihood estimation and the Fisher information matrix are studied.

Some Results on Weighted Distributions for Positive-Valued Random Variables

1987 ◽  
Vol 1 (4) ◽  
pp. 417-423 ◽  
Author(s):  
S. C. Kochar ◽  
R. P. Gupta
Keyword(s):  
Probability Distributions ◽  
Random Variables ◽  
Weighted Distributions ◽  
Partial Orderings

For nonnegative random variables, the weighted distributions have been compared with the original distributions with the help of partial orderings of probability distributions. Bounds on the moments of the weighted distributions have been obtained in terms of the moments of the original distributions for some nonparametric classes of aging distributions.

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